Table 6.
Prediction models | PRS CI-based (n = 1256) | PRS mean-based (n = 6012) |
---|---|---|
AUC (95% CI) | AUC (95% CI) | |
PRS > 90th vs. PRS < 10th (PRS risk) | 0.6076 (0.6055, 0.6082) | 0.5925 (0.5903, 0.5948) |
PRS risk + age | 0.6363 (0.63196, 0.63688) | 0.6094 (0.6093, 0.6097) |
PRS risk + age + gender | 0.6347 (0.6198, 0.6407) | 0.6088 (0.6041, 0.6106) |
PRS risk + age + gender + smoking status | 0.7104 (0.6980, 0.7191) | 0.6884 (0.6852, 0.6905) |
PRS risk + age + gender + packyears | 0.7299 (0.7179, 0.7388) | 0.7182 (0.7154, 0.7202) |
Age + gender + smoking status | 0.6584 (0.6562, 0.6610) | 0.6602 (0.6558, 0.6621) |
The prediction model performances incorporating different risk factors of PRS-based risk subgroup, age, gender, and smoking history were evaluated in subsets of individuals that were identified by the PRS CI-based approach and by the PRS mean-based approach. For the PRS CI-based approach, the models were constructed and evaluated in the individuals that can be identified with certainty (n = 1256). As a comparison, we constructed the same models and evaluated in the individuals that were classified as the lowest and highest risk by PRS-16-CV mean (n = 6012). The model performance was evaluated using five-fold cross-validation. Area under the curve (AUC) and 95% confidence intervals (CI) are shown